Transparency in Infectious Disease Research: Meta-research Survey of Specialty Journals

被引:2
|
作者
Zavalis, Emmanuel A. [1 ,2 ]
Contopoulos-Ioannidis, Despina G. [3 ]
Ioannidis, John P. A. [2 ,4 ,5 ,6 ]
机构
[1] Karolinska Inst, Dept Learning Informat Management & Ethics, Stockholm, Sweden
[2] Stanford Univ, Meta Res Innovat Ctr Stanford METR, Meta, Italy
[3] Stanford Univ, Sch Med, Div Infect Dis, Dept Pediat, Stanford, CA USA
[4] Stanford Univ, Sch Med, Stanford Prevent Res Ctr, Dept Med, Stanford, CA USA
[5] Stanford Univ, Sch Med, Dept Epidemiol & Populat Hlth, Stanford, CA USA
[6] Stanford Univ, Sch Med, 1265 Welch Rd,MSOB X306, Stanford, CA 94305 USA
来源
JOURNAL OF INFECTIOUS DISEASES | 2023年 / 228卷 / 03期
关键词
infectious disease; meta-research; reproducibility; rigor; transparency; AUTHORS;
D O I
10.1093/infdis/jiad130
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
An evaluation of 5340 articles published in 9 specialty infectious disease journals in 2019 and 2021 showed code sharing, data sharing, registration, and conflicts of interest and funding disclosures in 3%, 11%, 8%, 79%, and 92%, respectively; transparency can be improved. Background Infectious diseases carry large global burdens and have implications for society at large. Therefore, reproducible, transparent research is extremely important. Methods We evaluated transparency indicators (code and data sharing, registration, and conflict and funding disclosures) in the 5340 PubMed Central Open Access articles published in 2019 or 2021 in the 9 most cited specialty journals in infectious diseases using the text-mining R package, rtransparent. Results A total of 5340 articles were evaluated (1860 published in 2019 and 3480 in 2021 [of which 1828 were on coronavirus disease 2019, or COVID-19]). Text mining identified code sharing in 98 (2%) articles, data sharing in 498 (9%), registration in 446 (8%), conflict of interest disclosures in 4209 (79%), and funding disclosures in 4866 (91%). There were substantial differences across the 9 journals: 1%-9% for code sharing, 5%-25% for data sharing, 1%-31% for registration, 7%-100% for conflicts of interest, and 65%-100% for funding disclosures. Validation-corrected imputed estimates were 3%, 11%, 8%, 79%, and 92%, respectively. There were no major differences between articles published in 2019 and non-COVID-19 articles in 2021. In 2021, non-COVID-19 articles had more data sharing (12%) than COVID-19 articles (4%). Conclusions Data sharing, code sharing, and registration are very uncommon in infectious disease specialty journals. Increased transparency is required.
引用
收藏
页码:227 / 234
页数:8
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